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update model card README.md
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README.md
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---
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license: cc-by-nc-4.0
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base_model: facebook/mms-1b-all
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tags:
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-mms-1b-all-lingala-ojpl-4
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: audiofolder
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type: audiofolder
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config: default
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split: train
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.2868821999256782
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-large-mms-1b-all-lingala-ojpl-4
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7849
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- Wer: 0.2869
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 3.5152 | 0.54 | 100 | 0.9315 | 0.3430 |
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| 0.4837 | 1.08 | 200 | 0.9377 | 0.3133 |
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| 0.5943 | 1.61 | 300 | 0.8318 | 0.3177 |
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| 0.6232 | 2.15 | 400 | 0.7491 | 0.3107 |
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| 0.5186 | 2.69 | 500 | 0.7888 | 0.2899 |
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| 0.6024 | 3.23 | 600 | 0.7674 | 0.2913 |
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| 0.4522 | 3.76 | 700 | 0.7849 | 0.2869 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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